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Record W1996428554 · doi:10.1111/0022-4537.00227

Immigrants' Perceptions of Housing Discrimination in Toronto: The Housing New Canadians Project

2001· article· en· W1996428554 on OpenAlexaffabout
Kenneth L. Dion

Bibliographic record

VenueJournal of Social Issues · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSomaliImmigrationHousing discriminationRental housingEthnic groupDemographic economicsPerceptionRentingRace (biology)Ethnic discriminationRacismPsychologySocioeconomicsPolitical scienceSociologyGender studiesEconomicsLaw

Abstract

fetched live from OpenAlex

The Housing New Canadians project investigated recent immigrants' perceptions of discrimination in finding rental housing since arriving in Toronto, Canada. Respondents from three immigrant communities —Jamaicans, Poles, and Somalis ά—indicated how much housing discrimination they had personally experienced and how much discrimination they perceived to have been directed toward their group. They also rated how much each of several factors, including race, income level, source of income, immigrant status, language, ethnic or national background, religion, and family size, contributed to each type of perceived discrimination. Jamaican and Somali immigrants perceived greater personal and group discrimination and also showed a greater discrepancy between personal and group discrimination than did Polish immigrants. Implications are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.369
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations114
Published2001
Admission routes2
Has abstractyes

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